預備知識
機器學習基石上及其作業零 (機率統計、線性代數、微分之基本知識)
參考書籍
Learning from Data: A Short Course , Abu-Mostafa, Magdon-Ismail, Lin, 2013.
參考文獻
G. Sever, A. Lee. Linear Regression Analysis, 2nd Edition, Wiley, 2003. (第九講：Linear Regression 由統計學的角度來分析；第十二到十三講：Polynomial Transform 後再做 Linear Regression)
D. C. Hoaglin, R. E. Welsch. The hat matrix in regression and ANOVA. American Statistician, 32:17–22, 1978. (第九講：Linear Regression 的 Hat Matrix)
D. W. Hosmer, Jr., S. Lemeshow, R. X. Sturdivant. Applied Logistic Regression, 3rd Edition, Wiley, 2013 (第十講：Logistic Regression 由統計學的角度來分析)
T. Zhang. Solving large scale linear prediction problems using stochastic gradient descent algorithms. International Conference on Machine Learning, (第十一講：Stochastic Gradient Descent 用在線性模型的理論分析)
R. Rifkin, A. Klautau. In Defense of One-Vs-All Classification. Journal of Machine Learning Research, 5: 101-141, 2004. (第十一講：One-versus-all)
J. Fürnkranz. Round Robin Classification. Journal of Machine Learning Research, 2: 721-747, 2002. (第十一講：One-versus-one)
L. Li, H.-T. Lin. Optimizing 0/1 loss for perceptrons by random coordinate descent. In Proceedings of the 2007 International Joint Conference on Neural Networks (IJCNN ’07), pages 749–754, 2007. (第十一講：一個由最佳化角度出發的 Perceptron Algorithm)
G.-X. Yuan, C.-H. Ho, C.-J. Lin. Recent advances of large-scale linear classification. Proceedings of IEEE, 2012. (第十一講：更先進的線性分類方法)
Y.-W. Chang, C.-J. Hsieh, K.-W. Chang, M. Ringgaard, C.-J. Lin. Training and testing low-degree polynomial data mappings via linear SVM. Journal of Machine Learning Research, 11(2010), 1471-1490. (第十二講：一個使用多項式轉換加上線性分類模型的方法)
M. Magdon-Ismail, A. Nicholson, Y. S. Abu-Mostafa. Learning in the presence of noise. In Intelligent Signal Processing. IEEE Press, 2001. (第十三講：Noise 和 Learning)
A. Neumaier, Solving ill-conditioned and singular linear systems: A tutorial on regularization, SIAM Review 40 (1998), 636-666. (第十四講：Regularization)
T. Poggio, S. Smale. The mathematics of learning: Dealing with data. Notices of the American Mathematical Society, 50(5):537–544, 2003. (第十四講：Regularization)
P. Burman. A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods. Biometrika, 76(3): 503–514, 1989. (第十五講：Cross Validation)
R. Kohavi. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Proceedings of the 14th International Joint Conference on Artificial intelligence (IJCAI ’95), volume 2, 1137–1143, 1995. (第十五講：Cross Validation)
A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. Occam’s razor. Information Processing Letters, 24(6):377–380, 1987. (第十六講：Occam's Razor)
后记，作为一个在985双一流大学读博士的我（大连理工大学），博一一年马上要结束了，和导师基本没说过话，导师基本也没见过，导师也是能说一个字绝不说两个字的，实验室的气氛十分的诡异，经过这一年的经历我是明白了这么一件事，那就是博士生在某种程度上真的是博导的廉价劳动力，不知道这条路是否能走下去，如果再选择的话我想我会慎重考虑是否读这个博士，所谓的科研又是什么，总之我想不管到什么时候成为领导的廉价劳力这绝对不是教育的本质。